We propose to use state of the art proteomics technologies and novel computational strategies to identify serum proteins that can detect the majority of women with serous ovarian cancer (SOC) three years before diagnosis. The rationale for our research plan follows from a set of factors, demonstrated in our preliminary work, which suggest that for SOC discovering biomarkers in plasma is feasible with the technologies and methodologies at our disposaL. These factors include the evidence that some serum proteins in SOC elevate two or more years before clinical diagnosis, and that our proteomics technologies are capable of identifying and measuring changes in the blood following OC development. Our research strategy is based on a hypothesis that the best performing biomarkers wil likely be those that measure the direct consequence of molecular alterations distinguishing ovarian cancer from normal cells and tissues, or even better, protein or peptide sequences that may be unique to women with OC. To identify these proteins we combine a proteomics approach capable of quantifying proteins below 1 ng/ml with unique data mining strategies that combine our SOC data with several other valuable sources of data, including: proteomic profiles of WHI blood from cancer-free women, and proteomic and genomic sequence and expression data measuring normal and tumor ovary cells. Together these data will permit us to identify which plasma proteins are possibly tumor derived, and low abundant in cancer-free women.